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Trust in Smart Personal Assistants: A Systematic Literature Review and Development of a Research Agenda
Abstract
Smart Personal Assistants (SPA) fundamentally influence the way individuals perform tasks, use services and interact with organizations. They thus bear an immense economic and societal potential. However, a lack of trust - rooted in perceptions of uncertainty and risk - when interacting with intelligent computer agents can inhibit their adoption. In this paper, we conduct a systematic literature review to investigate the state of knowledge on trust in SPAs. Based on a concept-centric analysis of 50 papers, we derive three distinct research perspectives that constitute this nascent field: user interface-driven, interaction-driven, and explanation-driven trust in SPAs. Building on the results of our analysis, we develop a research agenda to spark and guide future research surrounding trust in SPAs. Ultimately, this paper intends to contribute to the body of knowledge of trust in artificial intelligence-based systems, specifically SPAs. It does so by proposing a novel framework mapping out their relationship.
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“This has helped identify factors contributing to positive or negative user experience [118] and has addressed specific aspects such as trust [119], perceived social support [71], human likeness [4], and how these aspects are impacted by chatbot design [42].”
From Future directions for chatbot research: An interdisciplinary research agenda (2021) · cites this paper as [119]
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Cited by
Sorted by citations
Trust in AI: progress, challenges, and future directions
Afroogh, S., Akbari, A., Malone, E., Kargar, M., & Alambeigi, H. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-04044-8 · Cited by 718
“…2021; Hui et al., 2021; Jacobs et al., 2021; D. K. D. Kim and Kim, 2021a), fi nance (Chandra et al., 2010; Kumar et al., 2021; Zierau et al., 2021), personal assistance (Fan et al., 2021b; Pitardi and Marriott, 2021a; Zierau et al., 2020), autonomous vehicles (Ajenaghughrure et al., 2020a), etc.”
Future directions for chatbot research: An interdisciplinary research agenda
Følstad, A., Araujo, T., Law, E. L.-C., Brandtzaeg, P. B., Papadopoulos, S., Reis, L., Baez, M., Laban, G., McAllister, P., Ischen, C., et al. (2021) · Computing · doi:10.1007/s00607-021-01016-7 · Cited by 247
“This has helped identify factors contributing to positive or negative user experience [118] and has addressed specific aspects such as trust [119], perceived social support [71], human likeness [4], and how these aspects are impacted by chatbot design [42].”
BackgroundHornung, O., & Smolnik, S. (2021) · Electronic Markets · doi:10.1007/s12525-021-00493-0 · Cited by 98
“Regarding PVAs, trust and privacy issues mostly lead to users rejecting this technology (Cho et al., 2020; Liao et al., 2019; Zierau et al., 2020).”
BackgroundEthical Design of Conversational Agents: Towards Principles for a Value-Sensitive Design
Wambsganß, T., Höch, A., Zierau, N., & Söllner, M. (2021) · Lecture notes in information systems and organisation · doi:10.1007/978-3-030-86790-4_37 · Cited by 31
“Thus, a plethora of positive user outcomes have been recorded, such as engagement [4], trust [5, 6], rapport, and ease of use, in several domains, such as education [7–9], healthcare [10] and customer service [11, 12].”
BackgroundSelf-citationMicroexpressions in digital humans: perceived affect, sincerity, and trustworthiness
Tastemirova, A., Schneider, J., Kruse, L. C., Heinzle, S., & Brocke, J. V. (2022) · Electronic Markets · doi:10.1007/s12525-022-00563-x · Cited by 35
“Digital humans are increasingly built to establish emotional bonds, where friendly style and social-emotional cues positively influence the perceived trustworthiness and level of interactivity (Zierau et al., 2020).”
BackgroundZierau, N., Flock, K., Janson, A., Söllner, M., & Leimeister, J. M. (2021) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2021.666 · Cited by 26
“Although IS research has investigated trust in various technologies for a long time [26], further research addressing trust in chatbots is needed [27].”
BackgroundSelf-citationSatori 悟り: Towards Proactive AR Assistant with Belief-Desire-Intention User Modeling
Li, C., Wu, G., Chan, G. Y.-Y., Turakhia, D. G., Castelo, S., Li, D., Welch, L., Silva, C. T., & Qian, J. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714188 · Cited by 49
“Their ideas and designs motivated later system implementations.”
Knote, R., Janson, A., Söllner, M., et al. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3923706 · Cited by 19
Self-citation(Why) Do We Trust AI?: A Case of AI-based Health Chatbots
Prakash, A. V., & Das, S. (2024) · AJIS. Australasian journal of information systems/AJIS. Australian journal of information systems/Australian journal of information systems · doi:10.3127/ajis.v28.4235 · Cited by 21
An Interactional Account of Empathy in Human-Machine Communication
Concannon, S. J., Roberts, I., & Tomalin, M. (2023) · Human-Machine Communication · doi:10.30658/hmc.6.6 · Cited by 16
Krop, P., Koch, M. J., Carolus, A., Latoschik, M. E., & Wienrich, C. (2024) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3613905.3650749 · Cited by 20
“The design of these systems, i.e., the external appearance of avatars, agents, or robots, can have a massive influence on trust [31, 32, 35, 40, 59, 62].”
BackgroundChatting about the unaccepted: Self-disclosure of unaccepted news exposure behaviour to a chatbot
Ischen, C., Butler, J., & Ohme, J. (2023) · Behaviour and Information Technology · doi:10.1080/0144929x.2023.2237605 · Cited by 14
Building Trust Over Time in Human-Agent Relationships
Olson, D. M., & Xu, Y. (2021) · International Conference on Human-Agent Interaction (HAI) · doi:10.1145/3472307.3484178 · Cited by 8
“…for HAI researchers to address: “From a methodological perspective, as most of the identified studies are based on laboratory experiments, we recommend to increasingly use field experiments to ensure external validity and, thus, to be able to provide stronger insights for practitioners” [15].”
BackgroundAnton, E., Oesterreich, T. D., Schuir, J., & Teuteberg, F. (2022) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2022.714 · Cited by 4
“This anthropomorphic aspect of CAs alters the common interaction with the software component in sociotechnical systems, raising questions for researchers concerning the conditions under which CAs are adopted or rejected [6, 7, 8].”
BackgroundKammerlohr, V., & Paradice, D. (2022) · Nomos Verlagsgesellschaft mbH & Co. KG eBooks · doi:10.5771/9783957104106-19
Nonverbal Communication in the Metaverse
Matusitz, J., & Dacas, J. (2024) · Signals and communication technology · doi:10.1007/978-3-031-63485-7_5
Age and User Perceptions of Virtual Humans: A Survey-Based Analysis
Patil, P., & Mouli, S. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-16992-1_27
Metadata
- Authors
- University of St.Gallen, I. O. I. M., Zierau, N., Engel, C., Söllner, M., University of Kassel, I. S. A. S. E., Leimeister, J. M., & University of Kassel, I. S.
- Venue
- WI2020 Zentrale Tracks
- Publisher
- GITO Verlag
- Published
- 2020-03-09
- Pages
- 99-114
- OpenAlex
- W4230628669
- Cited by
- 17
- References
- 0
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 4 · 2023: 2 · 2022: 4 · 2021: 5
- FWCI
- 0.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Alexandria (UniSG) (University of St.Gallen) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Keywords
- smart personal assistants, trust in AI, user interface design, interaction design, explanation, uncertainty, risk perception, research agenda
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